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dc.contributor.authorManion, Steve Lawrence
dc.date.accessioned2010-04-09T04:39:44Z
dc.date.availableNO_RESTRICTIONen_US
dc.date.available2010-04-09T04:39:44Z
dc.date.issued2009
dc.identifier.urihttp://hdl.handle.net/10179/1237
dc.description.abstractThe quality of Machine Translation (MT) can often be poor due to it appearing incoherent and lacking in fluency. These problems consist of word ordering, awkward use of words and grammar, and translating text too literally. However we should not consider translations such as these failures until we have done our best to enhance their quality, or more simply, their fluency. In the same way various processes can be applied to touch up a photograph, various processes can also be applied to touch up a translation. This research outlines the improvement of MT quality through the application of Fluency Enhancement (FE), which is a process we have created that reforms and evaluates text to enhance its fluency. We have tested our FE process on our own MT system which operates on what we call the SAM fundamentals, which are as follows: Simplicity - to be simple in design in order to be portable across different languages pairs, Adaptability - to compensate for the evolution of language, and Multiplicity - to determine a final set of translations from as many candidate translations as possible. Based on our research, the SAM fundamentals are the key to developing a successful MT system, and are what have piloted the success of our FE process.en_US
dc.language.isoenen_US
dc.publisherMassey Universityen_US
dc.rightsThe Authoren_US
dc.subjectMachine translatingen_US
dc.subjectMachine translationen_US
dc.subject.otherFields of Research::280000 Information, Computing and Communication Sciences::280200 Artificial Intelligence and Signal and Image Processing::280205 Text processingen_US
dc.titleFluency enhancement : applications to machine translation : thesis for Master of Engineering in Information & Telecommunications Engineering, Massey University, Palmerston North, New Zealanden_US
dc.typeThesisen_US
thesis.degree.disciplineInformation and Telecommunications Engineeringen_US
thesis.degree.grantorMassey Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Engineering (M.E.)en_US


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